metadata

base_model: google/gemma-2-9b-it
datasets:
  - nroggendorff/eap
language:
  - en
license: mit
tags:
  - trl
  - sft
  - art
  - code
  - adam
  - mistral
model-index:
  - name: eap
    results: []
pipeline_tag: text-generation

Edgar Allen Poe LLM

EAP is a language model fine-tuned on the EAP dataset using Supervised Fine-Tuning (SFT) and Teacher Reinforced Learning (TRL) techniques.

Features

Utilizes SFT and TRL techniques for improved performance
Supports English language

Usage

To use the LLM, you can load the model using the Hugging Face Transformers library:

from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
import torch

bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_use_double_quant=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.bfloat16
)

model_id = "nroggendorff/gemma-eap"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config)

prompt = "[INST] Write a poem about tomatoes in the style of Poe.[/INST]"
inputs = tokenizer(prompt, return_tensors="pt")

outputs = model.generate(**inputs)

generated_text = tokenizer.batch_decode(outputs)[0]
print(generated_text)

License

This project is licensed under the MIT License.